Application of Automation and Machine Learning for Analytical Sciences Challenges in Pharmaceutical Research and Development

Description:
Recent advances and increased adoption of laboratory automation are accelerating the Pharmaceutical drug discovery and development process. These advancements have created a new set of unmet analytical challenges due in part to the variety and number of experimental samples being generated. This session uniquely combines both academic and industrial research to present state-of-the-art development of new approaches for these unmet challenges, including high throughput analytics, artificial intelligence modeling, and prediction techniques for chemical processes. The first portion of the session will focus on how machine learning can be utilized for high throughput analytical methods including chromatography and mass spectrometry. The seminar will then shift to using data generated in an automated environment to perform more accurate chemometric models and mechanistic models supported by artificial intelligence. The sessions provides a forum for engineers and scientists, from industry and academia, to share cutting-edge research and produce fruitful discussion on the use of robotics and machine learning in laboratory automation. This Pittcon symposium is a great opportunity to highlight the challenges for analytical scientists in the future of pharmaceutical R&D and the criticality of innovation in the field.

Speaker: Matthew Bahr - GlaxoSmithKline
Matthew Bahr is an Associate Fellow at GlaxoSmithKline, and currently leads a team of analytical scientists focused on pharmaceutical research using robotic high-throughput instrumentation. Dr. Bahr also sits on the Board of Directors for the Enabling Technologies Consortium, which emphasizes pharmaceutical collaborations in a pre-competitive environment.

For the first half of his career at GSK, Dr. Bahr oversaw the operations of two oral solid dosage pilot plants in the greater Philadelphia area. Following that, he transitioned into screening small drug molecules through the deployment of high-throughput analytical workflows, ensuring that the design and interpretation of complex experiments achieve the desired outcomes of project teams for pre-clinical through late-stage assets.